rs114046333 - LINC02571 - HLA-B
Magnitude 2.2 · 2 studies on file
Reported associations
-
Improved genetic discovery and fine-mapping resolution through multivariate latent factor analysis of high-dimensional traits - Unknown journal (n.d.) · Unknown authors · PubMed 40220762
ABSTRACT: Summary Genome-wide association studies (GWASs) of high-dimensional traits, such as blood cell or metabolic traits, often use univariate approaches, ignoring trait relationships. Biological mechanisms generating variation in high-dimensional traits can be captured parsimoniously through a GWAS of latent factors. Here, we introduce flashfmZero, a zero-correlation latent-factor-based multi-trait fine-mapping approach. In an application to 25 latent factors derived from 99 blood cell traits in the INTERVAL cohort, we show that latent factor GWASs enable the detection of signals generating sub-threshold associations with several blood cell traits. The 99% credible sets (CS99) from flashfmZero were equal to or smaller in size than those from univariate fine-mapping of blood cell trait
-
Genome-wide association and HLA region fine-mapping studies identify susceptibility loci for multiple common infections - Unknown journal (n.d.) · Unknown authors · PubMed 28928442
ABSTRACT: Infectious diseases have a profound impact on our health and many studies suggest that host genetics play a major role in the pathogenesis of most of them. We perform 23 genome-wide association studies for common infections and infection-associated procedures, including chickenpox, shingles, cold sores, mononucleosis, mumps, hepatitis B, plantar warts, positive tuberculosis test results, strep throat, scarlet fever, pneumonia, bacterial meningitis, yeast infections, urinary tract infections, tonsillectomy, childhood ear infections, myringotomy, measles, hepatitis A, rheumatic fever, common colds, rubella and chronic sinus infection, in over 200,000 individuals of European ancestry. We detect 59 genome-wide significant (P < 5 × 10−8) associations in genes with key roles
Auto-generated from study metadata. AI-synthesised commentary is added when this entry is regenerated through content-service's LLM mode.